1.1万 件 ・ 関連度順
概要と使いどころ
Adversarial spec-compliance PR review — cross-references diffs against approved specs, verifies runtime claims against source, detects competing PRs, audits scope/convention compliance. Use before merging.
日本語の概要は準備中です。原文の説明を表示しています。
Generates simulation inputs across fidelity levels — OpenFOAM CFD cases, ngspice netlists, interactive React artifacts, and FreeCAD FEM setups — from verified engineering calculations.
日本語の概要は準備中です。原文の説明を表示しています。
Kolla-Ansible deployment engine skill for containerized OpenStack lifecycle management. Use when bootstrapping, deploying, reconfiguring, or upgrading OpenStack environments. Covers globals.yml configuration, inventory management, container operations, rolling upgrades, password management, and troubleshooting deployment failures across all service containers. This is the meta-skill that manages the deployment lifecycle for all OpenStack services.
日本語の概要は準備中です。原文の説明を表示しています。
NASA Systems Engineering methodology mapped to cloud operations. Use when planning, executing, verifying, or documenting OpenStack cloud infrastructure following NASA SP-6105 and NPR 7123.1 processes. Provides phase gate criteria, document templates, and cross-references for all 7 SE lifecycle phases applied to cloud deployment and operations.
日本語の概要は準備中です。原文の説明を表示しています。
Mathematical verification for physical calculations: unit tracking algebra (exponent maps), PhysicalQuantity pattern for compound units, SI/Imperial mixed-unit handling, Buckingham pi theorem for dimensionless groups, and common engineering dimensionless numbers. Activates for unit verification, dimensional consistency checks, scaling analysis, and calculation validation across all infrastructure domains.
日本語の概要は準備中です。原文の説明を表示しています。
Add runtime UI options (select/checkbox/switch/input) to MaaFramework option surfaces such as `assets/interface.json` or `assets/resource/tasks/**/*.json`. Use when adding a user-facing toggle, selector, checkbox, or input; wiring options to `pipeline_override`; aligning option paths with Python `context.get_node_data()` or CustomAction params; or reviewing option behavior across Pipeline JSON and Python.
日本語の概要は準備中です。原文の説明を表示しています。
A comprehensive guide for using ConfigHub to manage Kubernetes configuration across multiple environments using Configuration as Data principles. This rulebook covers installation, configuration management, variant handling, and operational workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Condensed ANIMA on quantum-classical and classical-quantum networks. All skill compositions materialized as s-expressions across the polyglot substrate.
日本語の概要は準備中です。原文の説明を表示しています。
GF(3) color envelope preservation across navigator compositions
日本語の概要は準備中です。原文の説明を表示しています。
Generalization and composition of constraints across navigators
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," or "CTA copy." For email copy, see email-sequence. For popup copy, see popup-cro.
日本語の概要は準備中です。原文の説明を表示しています。
Maps the 18 OCapN/CapTP/E-rights patterns reinvented piecemeal across codex-rs to their canonical Spritely/Goblins equivalents and the hermes-* bridge skills that formalize each correspondence. Use when auditing capability architecture in codex-rs, planning a Hoot/Goblins port, or reasoning about which E-rights primitive a codex-rs module implicitly implements.
日本語の概要は準備中です。原文の説明を表示しています。
GitHub interactome explorer for bmorphism/plurigrid ecosystem. Maps collaborations across AlgebraicJulia, Topos Institute, Anthropic, and MCP servers. Use for discovering cobordisms between research communities.
日本語の概要は準備中です。原文の説明を表示しています。
Complement to alice-emacs-mods. Covers what alice does not — ghostel mastery, multi-daemon orchestration, cross-session coordination, debug/recovery harness, REPL-as-dynamical-citizen, QRTP distribution, strobe internals, and the hard-won lessons from spawning and debugging live REPLs under the server daemon. Read alongside alice-emacs-mods; together they tile the total Emacs-mod space on this machine.
日本語の概要は準備中です。原文の説明を表示しています。
Bisimulation game for resilient skill dispersal across AI agents with GF(3) conservation and observational bridge types.
日本語の概要は準備中です。原文の説明を表示しています。
Go-based security techniques from "Black Hat Go" extended with macOS, Cloud, Mobile, IoT, Supply Chain, API, Web3, AI/ML, Red Team, ATT&CK, and LLM chapters. 186 techniques, 36 tools, 33 defenses across 37 chapters. Includes adversarial bisimulation games with Ungar (order-dependent) and join-semilattice structures. AAIF-compatible multiplayer agent games for human-agent security exercises.
日本語の概要は準備中です。原文の説明を表示しています。
Category Theory Tripartite: SICP generic dispatch, CTP Racket categories, CatColab double theories across 3 parallel worldlines with GF(3) conservation
日本語の概要は準備中です。原文の説明を表示しています。
Apply brand colors and typography to artifacts. Use when brand colors, style guidelines, visual formatting, or company design standards apply. Ensures consistency across branded content.
日本語の概要は準備中です。原文の説明を表示しています。
GF(3)-conserved distribution of Claude threads across Aptos worlds
日本語の概要は準備中です。原文の説明を表示しています。
Validates GF(3) conservation across triadic braindance replays. Ensures MINUS+ERGODIC+PLUS=0.
日本語の概要は準備中です。原文の説明を表示しています。
Unified messaging via three access tiers — MCP (live API), beeper-cli (authenticated CLI), and direct SQLite→DuckDB (full archive). Search, analyze, and act across all networks.
日本語の概要は準備中です。原文の説明を表示しています。
Measure encoding/decoding throughput across Syrup implementations. This skill provides bandwidth benchmarks for comparing serialization performance.
日本語の概要は準備中です。原文の説明を表示しています。
Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.
日本語の概要は準備中です。原文の説明を表示しています。